Adaptive MPI Translation For Multi-Site Image Exchange

Adaptive MPI Translation For Multi-Site Image Exchange

Patients visiting multiple specialists at multiple institutions are a common occurrence throughout the healthcare ecosystem that needs some special consideration from an information exchange perspective. When it comes to exchanging data, on the surface and under ideal conditions things may appear simple and straightforward. Institutions, however, face various implementation challenges and spend a lot of time and resources when bridging gaps between assumptions and realities. The amount and type of data collected during each patient visit dictate complexities and compromises involved in possible solutions. Transporting imaging exams in particular makes the task even more challenging.

Patients carrying their images on physical media works, but comes with drawbacks such as wasted time and money, as well as issues with security and confidentiality. Third party cloud-based image sharing services are becoming popular for one-on-one sharing. For limited numbers of exams, they do provide a good solution. However, between the source and the destination, there are several unknowns with respect to confidentiality, audit trail, and the number of copies that are left behind in the transfer. Furthermore, costs involved in manual or semi-automatic means of image ingestion into destination PACS are not insignificant. In high volume reading environments, imported external exams without optimal tag morphing pose challenges in hanging protocols and relevant priors, driving reading physician productivity down.

How do we automate this for a large number of exams across multiple institutions?

Conventional wisdom suggests creating an MPI strategy to transport images among subscribers. In an ideal environment, that works fine with a known MPI reference. However, strategic discussions between competing parties usually end up with no real solution. Simple things get complicated for a variety of reasons, especially when dealing with independent (and sometimes competing) institutions and multi-specialty groups. The ideal solution here is to have an independent and intelligent translator that can provide fast and automated image transfer across multiple institutions.

PICOM365 provides end to end image transfer with an adaptive translator.

It all starts when a new imaging order comes into the system from a facility. It triggers an event in our translation logic engine. The translation engine makes the decision based on an existing knowledge base and latest information from all connected sites. It then automatically pulls all relevant priors from all facilities and makes the prior exams ready at the originating facility. All this happens before the current exam reaches the local PACS. When the reading physician opens a new exam for reading, prior exams from one or more external facilities naturally appear in the viewer. End result – quality of care, productivity and physicians’ confidence in reporting increase due to this new access to comprehensive information. And every time a new mapping is formulated, it adds that piece of knowledge to the knowledge base and the system keeps learning.

Under the hood, this intelligent engine keeps pulling and pushing images across multiple facilities and keeps the entire clinical workflow productive with comprehensive reading packages.

Automated just-in-time priors need not be an item in your wish list, you can make it a reality with PICOM365.

ABOUT US

ScImage provides enterprise imaging and departmental PACS solutions for the healthcare industry. Founded in 1993, privately held, ScImage focuses on building customer loyalty to grow organically. Scalable from a single practice to multi-hospital enterprises, ScImage solutions are deployed on-premise, in the Cloud, or as a hybrid.